inst/doc/Data-Visualization.R
In doomlab/learnSTATS: Introduction to Statistics (ANLY 500)
## ---- include = FALSE----------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----eval = F------------------------------------
# textline +
# stat_summary(fun = mean,
# geom = "point") +
# stat_summary(fun = mean,
# geom = "line",
# aes(group = Group)) +
# stat_summary(fun.data = mean_cl_normal,
# geom = "errorbar",
# width = .2) +
# xlab("Measurement Time") +
# ylab("Mean Grammar Score") +
# cleanup +
# scale_color_manual(name = "Texting Option",
# labels = c("All the texts", "None of the texts"),
# values = c("Black", "Grey")) +
# scale_x_discrete(labels = c("Baseline", "Six Months"))
## ----echo=TRUE, message=FALSE, warning=FALSE-----
library(rio)
chickflick <- import("data/ChickFlick.sav")
str(chickflick)
## ------------------------------------------------
table(chickflick$gender)
table(chickflick$film)
## ----echo=TRUE, message=FALSE, warning=FALSE-----
chickflick$gender <- factor(chickflick$gender, #the variable you want to factor
levels = c(1,2), #the information already in the data
labels = c("Male", "Female")) #the labels for those levels
table(chickflick$gender)
## ------------------------------------------------
library(reshape) #note: you could also use pivot_longer in tidyverse
cricket <- import("data/Jiminy_Cricket.csv")
head(cricket)
## ------------------------------------------------
longcricket <- melt(cricket, #name of dataset
id = c("ID", "Strategy"),
measured = c("Success_Pre", "Success_Post"))
#you can actually leave measured blank
head(longcricket)
## ------------------------------------------------
colnames(longcricket)[3:4] #just to figure out which ones
colnames(longcricket)[3:4] <- c("Time", "Score")
## ---- echo = FALSE, out.width="35%", fig.align='center'----
knitr::include_graphics("pictures/graphs/badgraph.png")
## ---- echo = FALSE, out.width="35%", fig.align='center'----
knitr::include_graphics("pictures/graphs/bettergraph.png")
## ---- echo = FALSE, out.width="50%", fig.align='center'----
knitr::include_graphics("pictures/graphs/deception.png")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
library(ggplot2)
## ----eval = F------------------------------------
# #an example
# myGraph <- ggplot(dataset,
# aes(x_axis, y_axis,
# color = legend_var,
# fill = legend_var))
## ----eval = F------------------------------------
# #an example part 2
# myGraph +
# geom_bar() +
# geom_point() +
# xlab("X Axis Label") +
# ylab("Y Axis Label")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
crickethist <- ggplot(data = cricket, #dataset
aes(x = Success_Pre) #only define X axis
)
crickethist
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram()
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram(binwidth = 1)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram(binwidth = 1, color = 'purple', fill = 'magenta')
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram(binwidth = 1, color = 'purple', fill = 'magenta') +
xlab("Success Pre Test") +
ylab("Frequency")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
festival <- import("data/festival.csv")
str(festival)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
festivalhist <- ggplot(data = festival, aes(x = day1))
festivalhist +
geom_histogram(binwidth = 1, color = 'blue') +
xlab("Day 1 of Festival Hygiene") +
ylab("Frequency") +
theme_bw() #theme_classic() also good!
## ----echo=TRUE, message=FALSE, warning=FALSE-----
cleanup <- theme(panel.grid.major = element_blank(), #no grid lines
panel.grid.minor = element_blank(), #no grid lines
panel.background = element_blank(), #no background
axis.line.x = element_line(color = 'black'), #black x axis line
axis.line.y = element_line(color = 'black'), #black y axis line
legend.key = element_rect(fill = 'white'), #no legend background
text = element_text(size = 15)) #bigger text size
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
festivalhist +
geom_histogram(binwidth = 1, color = 'blue') +
xlab("Day 1 of Festival Hygiene") +
ylab("Frequency") +
cleanup
## ----echo=TRUE, message=FALSE, warning=FALSE-----
exam <- import("data/Exam_Anxiety.csv")
str(exam)
## ------------------------------------------------
table(exam$Gender)
exam$Gender <- factor(exam$Gender,
levels = c(1,2),
labels = c("Male", "Female"))
table(exam$Gender)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
scatter <- ggplot(exam, aes(Anxiety, Exam))
scatter +
geom_point() +
xlab("Anxiety Score") +
ylab("Exam Score") +
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
scatter + geom_point()+
geom_smooth(method = 'lm', color = 'black', fill = 'blue') +
xlab('Anxiety Score')+
ylab('Exam Score')+
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
scatter2 <- ggplot(exam, aes(Anxiety, Exam,
color = Gender, fill = Gender)) #why both?
scatter2 +
geom_point() +
geom_smooth(method = "lm") +
xlab("Anxiety Score") +
ylab("Exam Score") +
cleanup +
scale_fill_manual(name = "Gender of Participant",
labels = c("Men", "Women"),
values = c("purple", "grey")) +
scale_color_manual(name = "Gender of Participant",
labels = c("Men", "Women"),
values = c("purple", "grey10"))
## ------------------------------------------------
library(GGally)
ggpairs(data = exam[ , -1], #no participant variable
title = "Exam Anxiety, Scores, and Gender")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
str(chickflick) #already fixed gender
chickflick$film <- factor(chickflick$film,
levels = c(1,2),
labels = c("Bridget Jones", "Memento"))
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar <- ggplot(chickflick, aes(film, arousal))
chickbar +
stat_summary(fun = mean,
geom = "bar",
fill = "White",
color = "Black") +
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar +
stat_summary(fun = mean,
geom = "bar",
fill = "White",
color = "Black") +
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
position = position_dodge(width = 0.90),
width = 0.2) +
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar +
stat_summary(fun = mean,
geom = "bar",
fill = "White",
color = "Black") +
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
position = position_dodge(width = 0.90),
width = 0.2) +
xlab("Movie Watched by Participant") +
ylab("Arousal Level") +
cleanup +
scale_x_discrete(labels = c("Girl Film", "Guy Film"))
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar2 <- ggplot(chickflick, aes(film, arousal, fill = gender))
chickbar2 +
stat_summary(fun = mean,
geom = "bar",
position = "dodge") +
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
position = position_dodge(width = 0.90),
width = .2) +
xlab("Film Watched") +
ylab("Arousal Level") +
cleanup +
scale_fill_manual(name = "Gender of Participant",
labels = c("Boys", "Girls"),
values = c("Gray30", "Gray"))
## ----echo=TRUE, message=FALSE, warning=FALSE-----
hiccups <- import("data/Hiccups.csv")
str(hiccups)
## ----echo=TRUE, message=FALSE, warning=FALSE-----
longhiccups <- melt(hiccups,
measured = c("Baseline", "Tongue", "Carotid", "Other"))
str(longhiccups)
colnames(longhiccups) <- c("Intervention", "Hiccups")
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
hiccupline <- ggplot(longhiccups, aes(Intervention, Hiccups))
hiccupline +
stat_summary(fun = mean, ##adds the points
geom = "point") +
stat_summary(fun = mean, ##adds the line
geom = "line",
aes(group=1)) + ##necessary for mapping line to dots
stat_summary(fun.data = mean_cl_normal, ##adds the error bars
geom = "errorbar",
width = .2) +
xlab("Intervention Type") +
ylab("Number of Hiccups") +
cleanup
## ----echo=TRUE, message=FALSE, warning=FALSE-----
texting <- import("data/Texting.xlsx")
str(texting)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
texting$Group <- factor(texting$Group,
levels = c(1,2),
labels = c("Texting Allowed", "No Texting Allowed"))
longtexting <- melt(texting,
id = c("Group"),
measured = c("Baseline", "Six_months"))
str(longtexting)
colnames(longtexting) <- c("Group", "Time", "Grammar_Score")
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
textline <- ggplot(longtexting, aes(Time, Grammar_Score, color = Group))
textline +
stat_summary(fun = mean,
geom = "point") +
stat_summary(fun = mean,
geom = "line",
aes(group = Group)) + #Group is the variable name
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
width = .2) +
xlab("Measurement Time") +
ylab("Mean Grammar Score") +
cleanup +
scale_color_manual(name = "Texting Option",
labels = c("All the texts", "None of the texts"),
values = c("Black", "Grey")) +
scale_x_discrete(labels = c("Baseline", "Six Months"))
doomlab/learnSTATS documentation built on June 9, 2022, 12:54 a.m.
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## ---- include = FALSE----------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----eval = F------------------------------------
# textline +
# stat_summary(fun = mean,
# geom = "point") +
# stat_summary(fun = mean,
# geom = "line",
# aes(group = Group)) +
# stat_summary(fun.data = mean_cl_normal,
# geom = "errorbar",
# width = .2) +
# xlab("Measurement Time") +
# ylab("Mean Grammar Score") +
# cleanup +
# scale_color_manual(name = "Texting Option",
# labels = c("All the texts", "None of the texts"),
# values = c("Black", "Grey")) +
# scale_x_discrete(labels = c("Baseline", "Six Months"))
## ----echo=TRUE, message=FALSE, warning=FALSE-----
library(rio)
chickflick <- import("data/ChickFlick.sav")
str(chickflick)
## ------------------------------------------------
table(chickflick$gender)
table(chickflick$film)
## ----echo=TRUE, message=FALSE, warning=FALSE-----
chickflick$gender <- factor(chickflick$gender, #the variable you want to factor
levels = c(1,2), #the information already in the data
labels = c("Male", "Female")) #the labels for those levels
table(chickflick$gender)
## ------------------------------------------------
library(reshape) #note: you could also use pivot_longer in tidyverse
cricket <- import("data/Jiminy_Cricket.csv")
head(cricket)
## ------------------------------------------------
longcricket <- melt(cricket, #name of dataset
id = c("ID", "Strategy"),
measured = c("Success_Pre", "Success_Post"))
#you can actually leave measured blank
head(longcricket)
## ------------------------------------------------
colnames(longcricket)[3:4] #just to figure out which ones
colnames(longcricket)[3:4] <- c("Time", "Score")
## ---- echo = FALSE, out.width="35%", fig.align='center'----
knitr::include_graphics("pictures/graphs/badgraph.png")
## ---- echo = FALSE, out.width="35%", fig.align='center'----
knitr::include_graphics("pictures/graphs/bettergraph.png")
## ---- echo = FALSE, out.width="50%", fig.align='center'----
knitr::include_graphics("pictures/graphs/deception.png")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
library(ggplot2)
## ----eval = F------------------------------------
# #an example
# myGraph <- ggplot(dataset,
# aes(x_axis, y_axis,
# color = legend_var,
# fill = legend_var))
## ----eval = F------------------------------------
# #an example part 2
# myGraph +
# geom_bar() +
# geom_point() +
# xlab("X Axis Label") +
# ylab("Y Axis Label")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
crickethist <- ggplot(data = cricket, #dataset
aes(x = Success_Pre) #only define X axis
)
crickethist
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram()
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram(binwidth = 1)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram(binwidth = 1, color = 'purple', fill = 'magenta')
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
crickethist +
geom_histogram(binwidth = 1, color = 'purple', fill = 'magenta') +
xlab("Success Pre Test") +
ylab("Frequency")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
festival <- import("data/festival.csv")
str(festival)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
festivalhist <- ggplot(data = festival, aes(x = day1))
festivalhist +
geom_histogram(binwidth = 1, color = 'blue') +
xlab("Day 1 of Festival Hygiene") +
ylab("Frequency") +
theme_bw() #theme_classic() also good!
## ----echo=TRUE, message=FALSE, warning=FALSE-----
cleanup <- theme(panel.grid.major = element_blank(), #no grid lines
panel.grid.minor = element_blank(), #no grid lines
panel.background = element_blank(), #no background
axis.line.x = element_line(color = 'black'), #black x axis line
axis.line.y = element_line(color = 'black'), #black y axis line
legend.key = element_rect(fill = 'white'), #no legend background
text = element_text(size = 15)) #bigger text size
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
festivalhist +
geom_histogram(binwidth = 1, color = 'blue') +
xlab("Day 1 of Festival Hygiene") +
ylab("Frequency") +
cleanup
## ----echo=TRUE, message=FALSE, warning=FALSE-----
exam <- import("data/Exam_Anxiety.csv")
str(exam)
## ------------------------------------------------
table(exam$Gender)
exam$Gender <- factor(exam$Gender,
levels = c(1,2),
labels = c("Male", "Female"))
table(exam$Gender)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
scatter <- ggplot(exam, aes(Anxiety, Exam))
scatter +
geom_point() +
xlab("Anxiety Score") +
ylab("Exam Score") +
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
scatter + geom_point()+
geom_smooth(method = 'lm', color = 'black', fill = 'blue') +
xlab('Anxiety Score')+
ylab('Exam Score')+
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
scatter2 <- ggplot(exam, aes(Anxiety, Exam,
color = Gender, fill = Gender)) #why both?
scatter2 +
geom_point() +
geom_smooth(method = "lm") +
xlab("Anxiety Score") +
ylab("Exam Score") +
cleanup +
scale_fill_manual(name = "Gender of Participant",
labels = c("Men", "Women"),
values = c("purple", "grey")) +
scale_color_manual(name = "Gender of Participant",
labels = c("Men", "Women"),
values = c("purple", "grey10"))
## ------------------------------------------------
library(GGally)
ggpairs(data = exam[ , -1], #no participant variable
title = "Exam Anxiety, Scores, and Gender")
## ----echo=TRUE, message=FALSE, warning=FALSE-----
str(chickflick) #already fixed gender
chickflick$film <- factor(chickflick$film,
levels = c(1,2),
labels = c("Bridget Jones", "Memento"))
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar <- ggplot(chickflick, aes(film, arousal))
chickbar +
stat_summary(fun = mean,
geom = "bar",
fill = "White",
color = "Black") +
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar +
stat_summary(fun = mean,
geom = "bar",
fill = "White",
color = "Black") +
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
position = position_dodge(width = 0.90),
width = 0.2) +
cleanup
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar +
stat_summary(fun = mean,
geom = "bar",
fill = "White",
color = "Black") +
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
position = position_dodge(width = 0.90),
width = 0.2) +
xlab("Movie Watched by Participant") +
ylab("Arousal Level") +
cleanup +
scale_x_discrete(labels = c("Girl Film", "Guy Film"))
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
chickbar2 <- ggplot(chickflick, aes(film, arousal, fill = gender))
chickbar2 +
stat_summary(fun = mean,
geom = "bar",
position = "dodge") +
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
position = position_dodge(width = 0.90),
width = .2) +
xlab("Film Watched") +
ylab("Arousal Level") +
cleanup +
scale_fill_manual(name = "Gender of Participant",
labels = c("Boys", "Girls"),
values = c("Gray30", "Gray"))
## ----echo=TRUE, message=FALSE, warning=FALSE-----
hiccups <- import("data/Hiccups.csv")
str(hiccups)
## ----echo=TRUE, message=FALSE, warning=FALSE-----
longhiccups <- melt(hiccups,
measured = c("Baseline", "Tongue", "Carotid", "Other"))
str(longhiccups)
colnames(longhiccups) <- c("Intervention", "Hiccups")
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
hiccupline <- ggplot(longhiccups, aes(Intervention, Hiccups))
hiccupline +
stat_summary(fun = mean, ##adds the points
geom = "point") +
stat_summary(fun = mean, ##adds the line
geom = "line",
aes(group=1)) + ##necessary for mapping line to dots
stat_summary(fun.data = mean_cl_normal, ##adds the error bars
geom = "errorbar",
width = .2) +
xlab("Intervention Type") +
ylab("Number of Hiccups") +
cleanup
## ----echo=TRUE, message=FALSE, warning=FALSE-----
texting <- import("data/Texting.xlsx")
str(texting)
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
texting$Group <- factor(texting$Group,
levels = c(1,2),
labels = c("Texting Allowed", "No Texting Allowed"))
longtexting <- melt(texting,
id = c("Group"),
measured = c("Baseline", "Six_months"))
str(longtexting)
colnames(longtexting) <- c("Group", "Time", "Grammar_Score")
## ----echo=TRUE, fig.height=4, fig.width=8, message=FALSE, warning=FALSE----
textline <- ggplot(longtexting, aes(Time, Grammar_Score, color = Group))
textline +
stat_summary(fun = mean,
geom = "point") +
stat_summary(fun = mean,
geom = "line",
aes(group = Group)) + #Group is the variable name
stat_summary(fun.data = mean_cl_normal,
geom = "errorbar",
width = .2) +
xlab("Measurement Time") +
ylab("Mean Grammar Score") +
cleanup +
scale_color_manual(name = "Texting Option",
labels = c("All the texts", "None of the texts"),
values = c("Black", "Grey")) +
scale_x_discrete(labels = c("Baseline", "Six Months"))
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